Data Scientist

Summary

National Veterinary Associates (NVA) is a community of veterinary hospitals focused on providing excellent, accessible veterinary care. The Data Scientist will build and deploy agentic AI solutions that automate business processes, while also developing statistics and machine learning models for customer data to support better business decisions.

Responsibilities

• Build agentic AI solutions that automate manual, repetitive processes for the business teams they support, improving efficiency and accelerating business decisions
• Work hands-on with advanced AI platforms (Anthropic Claude, OpenAI, Google Gemini) to design and build agentic workflows, selecting the right models, tools, and frameworks for each use case
• Own end-to-end architecture design for agentic solutions—components, integrations, data flows, guardrails, and safe-deployment patterns—and document architecture plans for each version of the build
• Gather requirements directly from business stakeholders, translate business problems into technical solutions, and collaborate closely with them throughout design, build, and rollout
• Follow the standards, best practices, and guardrails established by the Data & Analytics organization to ensure solutions are safe, compliant, maintainable, and consistent with enterprise AI practices
• Partner closely with the IT Security team, keeping them informed and engaged on any externally facing agentic solution to ensure secure, compliant deployment
• Maintain well-documented PRDs (product requirement documents) and architecture plans for every version of each solution build, keeping documentation current as solutions evolve
• Perform dependency mapping across systems, data sources, models, and services to de-risk builds and ensure reliable integration
• Own incident response for deployed solutions—monitoring, triage, root-cause analysis, and remediation—to keep agentic solutions reliable and trustworthy in production
• Conduct detailed analysis of customer data and build data science / machine learning models—including customer lifetime value (LTV), client segmentation and classification, next best action, and pricing models—to drive better business decisions
• Communicate progress, risks, dependencies, and outcomes to the right stakeholders, including the Senior Manager, AI and business stakeholders, ensuring alignment throughout delivery
• Continuously evaluate emerging AI models, agentic frameworks, and tooling, applying them to improve the speed, quality, and safety of solutions delivered to business teams

Skills

• • 4+ years of hands-on experience building AI/ML or software solutions in production, including recent experience developing LLM-powered or agentic applications
• • Strong programming skills (e.g., Python) and experience integrating with advanced AI platforms and APIs such as Anthropic Claude, OpenAI, and Google Gemini—including prompt engineering, tool/function calling, retrieval, and agent orchestration frameworks
• • Solid foundation in statistics and machine learning, with demonstrated experience building applied models such as customer lifetime value, segmentation/classification, next best action, propensity, or pricing—and comfort with the full modeling lifecycle from data analysis through deployment
• • Experience designing solution architecture and integrating with enterprise data platforms, APIs, and cloud services (e.g., Azure), with an understanding of AI safety, responsible-AI, and secure-deployment practices and a track record of partnering with security teams on externally facing applications
• • Excellent documentation and communication skills—able to produce clear PRDs and architecture plans, gather requirements directly from stakeholders, and deliver iteratively in close collaboration with business stakeholders
• Location: Remote-friendly. Must be able to collaborate across U.S. time zones
• Travel: Minimal. May be once a quarter for stakeholder meetings

Qualifications

Must Haves

• • 4+ years of hands-on experience building AI/ML or software solutions in production, including recent experience developing LLM-powered or agentic applications
• • Strong programming skills (e.g., Python) and experience integrating with advanced AI platforms and APIs such as Anthropic Claude, OpenAI, and Google Gemini—including prompt engineering, tool/function calling, retrieval, and agent orchestration frameworks
• • Solid foundation in statistics and machine learning, with demonstrated experience building applied models such as customer lifetime value, segmentation/classification, next best action, propensity, or pricing—and comfort with the full modeling lifecycle from data analysis through deployment
• • Experience designing solution architecture and integrating with enterprise data platforms, APIs, and cloud services (e.g., Azure), with an understanding of AI safety, responsible-AI, and secure-deployment practices and a track record of partnering with security teams on externally facing applications
• • Excellent documentation and communication skills—able to produce clear PRDs and architecture plans, gather requirements directly from stakeholders, and deliver iteratively in close collaboration with business stakeholders
• Location: Remote-friendly. Must be able to collaborate across U.S. time zones
• Travel: Minimal. May be once a quarter for stakeholder meetings

Benefits

• Annual performance bonus
• Comprehensive health benefits (medical, dental, vision)
• 401(k) with company match
• Generous PTO
• Professional development opportunities
• Remote-friendly work arrangement